LiDAR Protective Screen Contamination Detection Using Sector Noise
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Solution Overview
Problem
Existing methods for identifying contamination on Lidar sensor protective screens are inadequate, leading to performance degradation and reduced accuracy in automated and autonomous vehicles and robots.
Innovation Solution
The detection region of the Lidar sensor is divided into sectors, with sector-specific background noise analysis conducted at varying sensitivities to reliably detect contamination by comparing sector noise levels against detection region noise levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the detection region is divided into multiple sectors for sector-specific analysis, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The detection region is divided into multiple sectors, with each sector independently analyzed for background noise levels. This segmentation enables localized contamination detection by comparing sector-specific noise characteristics against reference values, thereby improving measurement precision without requiring complex additional hardware.
2Reliability
If background noise is measured at various receiver sensitivities, then reliability is improved, but use of energy increases
Solution Approach 1:
The receiver sensitivity is varied periodically across multiple measurement cycles. Background noise is measured at different sensitivity levels in successive periods, allowing reliable contamination identification through comparison while distributing energy consumption over time rather than requiring simultaneous high-power measurements at all sensitivity levels.
3Measurement precision
If sector-specific background noise analysis is performed, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs background noise analysis on selected sectors or regions rather than uniformly analyzing all detection regions. This partial action approach maintains measurement precision for critical areas while reducing overall detection time by focusing computational resources on sectors most likely to contain contamination or show anomalous noise patterns.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method allows for precise and efficient detection of contamination, enhancing the accuracy and reliability of Lidar sensor data, thereby improving the performance of automated and autonomous systems.
Implementation Method 1
Lidar sensors send out a laser pulse or laser beam
Implementation Method 2
detect its reflections from objects within a detection region
Implementation Method 3
a received input of reflected light or background light is reduced
Data Source
AI summary
A method and device for identifying contamination on a protective screen of a lidar sensor may involve determining a sector background noise in a particular sector of a detection region of the lidar sensor and a detection region background noise is determined in a remaining detection region or the entire detection region. Contamination in the sector in question is then determined if the sector background noise is significantly lower than the detection region background noise. Alternatively, or additionally, a sector background noise is determined in the sector in question at different sensitivities of a receiver of the lidar sensor, and contamination in the sector in question is then determined if a sector background noise determined with a higher sensitivity is not significantly higher than a sector background noise determined with a lower sensitivity.